Sunday, January 16, 2011

Martin Odersky's Scala Levels

I just saw Martin's post on levels of expertise in Scala, and Tony Morris's response. The concept of levels is something that many in the community have called for repeatedly, in order to help ease people - especially team members who may be a little put off by some of Scala's more advanced features - into the language more gently. I understand the motivation, but it has always struck me as somewhat odd. The reason is that I think one needs to have very compelling reason for such a significant change to be justified, especially a change from a mature, mainstream technology such as Java into one as new an immature as Scala. To being, I'll recount my experience with adding Python as a stable in my programming toolbox.

Learning Python

I dabbled it Python a lot before really using it extensively. Much of my initial usage basically amounted to using Jython as a repl for interactively poking at Java libraries, especially ones that weren't particularly well documented. I thought Python was neat, but at the time most of my programming experience was in C++ and Java. I valued static typing. I valued having a compiler. When I was in college, I had a professor who said something along the line so of "The compiler is your friend. Write your code so that the compiler is more likely to catch your mistakes. Don't try to trick it or bypass it." This was in the context of C++ programming, and given all the ways that one can shoot himself in the foot using C++, it always seemed like sage advice. So giving up have a compiler to catch my mistakes, and an explicit structure clearly present in my code, seemed like an awful lot to ask. Sure, Python is more concise, but in my opinion conciseness is often more a matter of how closely the libraries you're using match the problem that you are trying to solve. About a year ago I had some experimental Python code that I had thrown together that did some regular expression heavy text processing then some XML processing (I was processing output of an application that produced invalid XML, so the first phase was the fix it so the XML parser wouldn't crash and the second was to actually process it). I can't remember why, but I decided to convert it to Java. I think it was because I wanted to integrate it with something that integrated well with Java, but not as well with Python. Anyway, the point is that the Python code and the Java code weren't that different in length. Sure, Java has a lot more boiler plate, but once your code starts being dominated by actual logic instead of getters and setters, it's the libraries that make the difference.

Anyway, I didn't really get into Python until I discovered and thoroughly learned metaclasses and descriptors. In my mind, they took Python from being a toy with a clean syntax to a language that opened up an entire new dimension of abstraction. A dimension of abstraction that had been missing all me life. A dimension that I had glimpsed in C++ template metaprogramming but had never quite managed to enter. All of a sudden I had this tool that enabled me to drastically and repeatedly reduce code sizes all while making the business logic cleaner and more explicit. I had a means to encode my ideas such that they enabled my coworkers to use them without fulling understanding them (an admittedly dangerous proposition). It was beautiful! They remain an important part of my toolbox to this day.

Incidentally, my first uses metaclasses and descriptors was to concisely implement immutable, lazy data structures. This was long before I knew anything about functional programming.

Learning Scala

I also dabbled in Scala a lot before really becoming enamored with it. I was caught by the conciseness over Java, especially the absence of getters and setters, the presence of operator overloading, and multiple inheritance using traits. But I had operator overloading and multiple inheritance in both C++ and Python. I could usually abstract away explicit getters and setters in Python, and by the time I started picking up Scala I had already made a significant shift towards immutability and laziness, so setters weren't as necessary. Scala was neat, and the compatibility with Java was a real benefit, but at first it didn't seem compelling. In fact, when I first started experimenting with Scala it seemed too buggy to really be worth it. Something worth watching, but not yet worth using. Also, by the time I started learning Scala I had already learned Common Lisp and functional programming with full tail-call optimization seemed awkward (and still does).

What eventually sold me on Scala was higher-kinded types, companion objects, and objects-as-modules. You see, but the time I started picking up Scala I had already developed a habit of using a lot of generic programming. This is easy in Python where there's no compiler check a type system to tell you that you are wrong. But a lot of the patterns I commonly used couldn't be translated into Java generics (in fact, in my first foray into Java generics I crashed javac writing code that was compliant with the Java specification). Scala gave me concise programs and type safety! And with the introduction of collections that actually use higher-kinded types in 2.8.0, along with the leaps and bounds made in robustness, I think it finally reached threshold for serious use.

That's not to say these are the only key features. Understanding folds was a real eureka moment for me. I'm not sure how one can do effective functional programming without them, but perhaps there is a way. Implicit definitions are also key, and they are used so extensively in Scala libraries that I think writing Scala without a decent understanding of them is nothing short of voodoo programming. In short, there's a lot, and the features tend combine together in powerful ways.

Summary

I understand the motivation for establishing levels, but I personally think if one avoids many of the features that Martin has flagged as advanced, then the benefits of Scala don't justify the risk of using such a new technology and the need to retrain people. I think without them one is better off finding a better library or framework for their current stack. Also, between the fact that advanced features are omnipresent in the libraries, and teams will always have someone who wants to use the more powerful features, avoiding them works a lot better in theory than it does in practice. You can't not use them, unless you don't use Scala's standard library and avoid almost any library written explicitly for Scala. You can only pretend that you are not using them.

This is probably going to get me flamed, but reward must justify risk. In many circumstances Scala has the features to justify the risk associated with it, but the justification quickly vanishes as the more powerful features are stripped away. So while I think a programmer may be productive at Martin's lower levels, they don't justify Scala over Java.

Sphere: Related Content